(1) Field of the Invention
The present invention relates to the fabrication of integrated circuit devices, and more particularly, to a method of monitoring tool performance using a multivariate advanced process control system in the fabrication of integrated circuit devices.
(2) Description of the Prior Art
Run by Run (RBR) feedback control schemes have been used widely to control and monitor the semiconductor manufacturing processes. Statistical process control is combined with feedback control and uses data from past runs to adjust the recipe for the next run. This method offers the potential for reducing process variability caused by equipment aging, chemical depletion, or fluctuation in ambient conditions with a minimal cost. Most literature in the RBR control, however, is only applicable to the manufacturing process with a single product by a single tool. For a foundry industry, due to different customer requirements, one of the most popular production styles is multiple products by multiple tools. For example, if a process runs eight products by five tools, then there are forty combinations which will lead to a very complex situation using conventional RBR control schemes. If separate feedback schemes are set up for each combination, besides affecting the efficiency of the RBR control schemes, this method also ignores the useful information between the tools and products. For example, under a specific tool, an individual control scheme does feedback only on a specific product and it loses the opportunity to adjust for other products produced by the same tool. In addition, since customer orders may not be continuous and scheduled tool set-up may change from time to time, the feedback scheme for any production lot cannot be successfully applied to the next production lot. Therefore, it is desired to provide a multiple run by run control process.
A number of patents address process control issues. For example, U.S. Pat. No. 5,963,902 to Wang uses an expectation maximization (EM) model in a pattern recognition process. U.S. Pat. No. 6,238,936 to Yu teaches mapping critical dimension (CD) of predetermined features at various process stages. A user can look at the data to see if adjustments should be made to an etching process. U.S. Pat. No. 5,757,673 to Osheiski et al teaches automated analysis of data from self-tests of steppers uploaded as an ASCII file. U.S. Pat. No. 6,245,581 to Bonser et al teaches a method of measuring critical dimension, analyzing the measurement, and performing a secondary etch process based on the analysis. U.S. Pat. No. 5,862,054 to Li shows a process parameter monitoring system. Statistical Process Control (SPC) analysis is performed on data from each machine. Results are displayed in graphical form. U.S. Pat. No. 6,263,255 to Tan et al discloses a software framework for measurement, processing, and strategy control of a factory. U.S. Pat. No. 5,243,377 to Umatate et al shows a lithography control system.